Files
SuperClaude/.claude/commands/spawn.md
NomenAK 219ff3905a feat: Optimize all 18 command files using @include reference system
Major streamlining achievement:
- Eliminate 2,733 lines of duplicate content across commands
- Reduce individual command files by ~70% (130-150 → 35-60 lines)
- Leverage existing shared/*.yml reference patterns
- Maintain full Claude Code compliance

Benefits:
• Single source of truth for universal content
• Guaranteed consistency across all commands
• Dramatically reduced maintenance overhead
• Massive token efficiency improvements

Implementation:
- Universal Legend: @include shared/universal-constants.yml#Universal Legend
- Universal Flags: @include shared/flag-inheritance.yml#Universal_Always
- Command patterns: References to appropriate shared/*.yml files
- Template system: Enhanced command-patterns.yml

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-06-24 22:46:52 +02:00

3.0 KiB

/spawn - Spawn focused agent for specialized tasks

Legend

@include shared/universal-constants.yml#Universal_Legend

Purpose

Spawn specialized sub-agents to handle specific tasks in $ARGUMENTS with focused expertise and parallel execution capabilities.

Syntax

/spawn [flags] [task-description]

@include shared/flag-inheritance.yml#Universal_Always

Core Flags

--agent flag:

  • researcher: Deep research & analysis
  • builder: Code generation
  • reviewer: Code review & QA
  • optimizer: Performance tuning
  • documenter: Documentation expert

--mode flag:

  • sequential: One agent at a time
  • parallel: Multiple agents
  • collaborative: Agents work together
  • supervisor: Oversee sub-agents

--scope flag:

  • focused: Single specific task
  • broad: Multiple related tasks
  • exploratory: Open-ended research
  • iterative: Refine through cycles

Agent Types

Researcher Agent:

  • Deep dive into topics
  • Compare solutions
  • Analyze trade-offs
  • Find best practices
  • Document findings

Builder Agent:

  • Generate code
  • Implement features
  • Create tests
  • Build prototypes
  • Integrate systems

Reviewer Agent:

  • Code quality checks
  • Security analysis
  • Performance review
  • Best practice validation
  • Suggest improvements

Optimizer Agent:

  • Performance profiling
  • Resource optimization
  • Algorithm improvements
  • Database tuning
  • Cache strategies

Documenter Agent:

  • API documentation
  • User guides
  • Code comments
  • Architecture docs
  • README files

Execution Modes

Sequential Mode:

Flow: Agent1 → Agent2 → Agent3
Use: When tasks depend on each other
Example: Research → Build → Review

Parallel Mode:

Flow: Agent1 | Agent2 | Agent3
Use: For independent tasks
Example: Multiple feature builds

Collaborative Mode:

Flow: Agents work together
Use: Complex problems
Example: System design session

Best Practices

Task Definition:

  • Clear objectives
  • Specific deliverables
  • Success criteria
  • Resource limits
  • Time constraints

Agent Selection:

  • Match expertise to task
  • Consider dependencies
  • Plan coordination
  • Set boundaries
  • Define handoffs

Coordination:

  • Clear communication
  • Shared context
  • Progress tracking
  • Result integration
  • Quality control

Examples

# Research then implement
/spawn --agent researcher "OAuth 2.0 best practices"
/spawn --agent builder "Implement OAuth based on research"

# Parallel feature development
/spawn --mode parallel --agent builder "User auth, Profile API, Settings UI"

# Full cycle with review
/spawn --mode sequential "Research → Build → Review payment integration"

# Collaborative system design
/spawn --mode collaborative --ultrathink "Design microservices architecture"

Integration

Works with:

  • All command flags pass through
  • Inherits persona preferences
  • Shares project context
  • Accumulates findings
  • Coordinates outputs

Deliverables

  • Agent execution logs
  • Task completion reports
  • Integrated results
  • Performance metrics
  • Lessons learned
  • Handoff documentation